By Jadd Elliot Dib, Founder & CEO, Pangaea X
Data and data analytics are increasingly playing a vital role across various sectors, including agriculture. Today, people can enjoy efficient delivery of their favourite agricultural produce, thanks to the modern food supply chain that relies heavily on data analytics.
Large-scale agriculture involves managing large quantities of inputs and outputs, which generates a huge number of data points. To improve the productivity of crops and livestock, scientists are developing and deploying technologies such as drones, internet of things (IoT) sensors, with machine learning being used to gather and process these data. These give farmers real-time information about their crops, the weather, and soil conditions, leading to enhanced decision-making and productivity.
The success of modern agriculture relies on being able to extract and analyse the data and act on the insights obtained – something easier said than done due to fragmented data and technology inequalities. Nonetheless, it is important to harness the capabilities of data analytics to tackle various challenges in feeding the global population, which is fast approaching 8.2 billion.
Among the most important factors in agriculture are the climate and the weather. Knowledge of climate and weather patterns gained over thousands of years have been passed down by farmers, dictating planting and harvesting schedules. Unfortunately, numerous famines throughout history were caused by weather anomalies, such as droughts or floods. With modern weather satellite imagery and other meteorological technologies, farmers are now able to predict and prepare for weather disturbances. This is especially important as climate change moves humanity into uncharted territory and poses significant threat to global food security. Such a scenario makes it imperative for agricultural scientists to acquire greater knowledge more rapidly and be able to identify data patterns to find out what works and what doesn’t and allow farmers to adapt accordingly.
Large-scale agriculture uses tremendous amount of resources, such as land, energy, water, and fertilisers, with agricultural waste posing a significant environmental concern. With proper data analysis, farmers can identify areas where inefficiency and wastage are high and take corrective measures, giving rise to precision farming. One example is the use of an IoT-enabled precision irrigation system that can reduce water consumption by 30% while producing larger yields. On the other hand, practices such as restorative agriculture, integrated pest management, and agroecology require a more intimate understanding of how nature works – and what better way to achieve this than through accurate data.
Another positive side effect of increased efficiency is profitability, which can stimulate more investments into data-driven agriculture, especially with consumer preferences leaning towards more organic and ethical farming practices. Clearly, as digital technology and data analytics continue to advance, their contributions to strengthening agriculture and food production are becoming more crucial.
Jadd Elliot Dib is the founder of data analytics platform Pangaea X, which allows clients from all industries to access high-quality, specialised data analytics talent.
